Fake image and video detection using capsule network

Smitha P; Varun Srinivas Naik; Deepika R; Chaithra K M; B G Sumith Kumar

Fake image and video detection using capsule network

Authors: Smitha P, Varun Srinivas Naik , Deepika R, Chaithra K M, B G Sumith Kumar

Unique Paper ID: 152145
Volume: 8
Issue: 2
PageNo: 639-642

Keywords: forged state-of-the-art capsule network spoofs convolutional neural network

Abstract:
Attackers can now easily manufacture forged photos and movies thanks to recent developments in media generating algorithms. The development of a forged version of a single film collected from a social network can be done in real time using state-of-the-art technology. Although several methods for identifying faked photos and videos have been developed, they are often aimed at specific areas and quickly become obsolete as new types of attacks emerge. The method shown in this project use a capsule network to detect various types of spoofs, ranging from replay attacks utilizing printed images or recorded films to deep convolutional neural networks-based computer-generated videos. It broadens the scope of capsule networks' application beyond their original goal of tackling inverse graphics difficulties

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ISSN: 2349-6002
Volume: 8
Issue: 2
PageNo: 639-642

Fake image and video detection using capsule network

Available:https://ijirt.org/Article?manuscript=152145

Impact Factor
8.01 (Year 2024)

UGC Approved
Journal no 47859

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